Case Study: AI for Good
How I stepped out of my comfort zone to teach lean nonprofits how to 10x their impact using early AI workflows.
Background
In the summer of 2024—when generative AI was still a brand-new frontier for most small organizations—small and mid-sized nonprofits found themselves caught in a whirlwind of hype and anxiety. Operating with micro-staffs and stretched thin across fundraising and administration, these teams were deeply curious about AI but lacked the practical guidance to figure out how it could actually help them.
Through Catchafire, I stepped in as an AI Strategy Consultant to volunteer my time and bridge that gap. Across engagements with 3 nonprofit organizations and 18 participating staff members, this pro bono work provided strategic enablement that saved the organizations an estimated $5,740 in consulting fees (per verified Catchafire impact data).
The Problem
The immediate instinct for most lean teams was to view AI as a blunt-force content generator: type a prompt, copy-paste whatever generic text spits out, and hope it sounds like the organization.
The deeper operational challenge wasn’t a lack of tools—it was a lack of a framework. Staff members didn't know how to integrate AI into their actual daily workflows (like drafting board reports, organizing data, or optimizing social schedules) without losing their authentic human voice or running into data privacy pitfalls. Furthermore, as an introvert, stepping up to host interactive live workshops meant stepping well outside my comfort zone to guide these discussions.
$5,740 Saved
Per Non-Profit I Taught These Early AI Frameworks
The Strategy: Shifting the Paradigm
Rather than positioning myself as an untouchable tech guru, I approached the workshops as a fellow early experimenter and idea-sharer. The goal wasn’t to teach them more than they knew, but to show them how to use tools that were already available to make their daily work a little more efficient.
I structured the training around a practical mental model—breaking AI usage down into three core operational buckets:
Using AI as a "Google": Moving beyond basic search fatigue by using LLMs for advanced information gathering, citing trusted frameworks (like Harvard Business Review insights), and optimizing data/query formatting.
Using AI as an "Intern / Admin Assistant": Automating repetitive administrative drag—such as using voice-to-text to brain-dump messy monthly meeting notes and instantly organizing them into clean action items for leadership.
Using AI as a "Brainstorming Partner": Training staff on prompt engineering, role-based persona prompts, and content atomization (turning a single annual report or email into multi-channel social assets) while always keeping human oversight at the wheel.
We don’t use AI to replace human critical thinking; we use it to handle the friction so we can stay focused on our mission.
The Outcome
The workshops gave these resource-constrained teams a tangible framework to reclaim hours of administrative time each week.
A New Mental Model: The biggest breakthrough for attendees was realizing AI wasn't just an automated essay writer, but an active collaborative partner that could help expand their operational capacity.
Practical Empowerment: Provided actionable prompt templates, role-based personas, and workflow strategies that small teams could immediately plug into their day-to-day operations.
Personal Growth: Stepping out from behind the screen to facilitate live strategic enablement proved that operational leadership isn't just about managing internal systems—it's about empowering others to build clarity and confidence in their own workflows.
Curious about the training framework? Explore the Original AI Empowerment Lunch & Learn Deck.
